Quadro Virtual Workstation on Amazon Web Services Elastic Compute Cloud Quick Start Guide

Getting started information for all users of NVIDIA Quadro Virtual Workstation on AWS EC2.

1. Creating and Using an NVIDIA Quadro Virtual Workstation Instance from the Amazon Web Services Elastic Compute Cloud Marketplace

NVIDIA® Quadro® Virtual Workstation is an NVIDIA Virtual Machine Image (VMI) preconfigured with Quadro Virtual Workstation software and NVIDIA GPU hardware. The NVIDIA Quadro driver is preinstalled on the VMI and NVIDIA ensures that the image is always up to date with the latest Quadro ISV certifications, patches, and upgrades. Support and technical information to help you get started are available on the NVIDIA Quadro vWS on CSP Marketplace community forum and from additional resources.

1.1. Creating a GPU-Accelerated Virtual Workstation

Prepare for creating a GPU-accelerated virtual workstation from the Amazon Web Services Elastic Compute Cloud marketplace as follows:

  1. In a web browser, log on to Amazon EC2 console (https://console.aws.amazon.com/ec2/).
  2. Go to the NVIDIA Quadro Virtual Workstation listing for the guest OS that you want to use:

    Screen capture showing the NVIDIA Quadro Virtual Workstation Overview page

  3. Follow the View Details link to view hourly pricing for the Quadro Virtual Workstation software. There are also additional Amazon Web Services Elastic Compute Cloud infrastructure costs for the GPU, memory, and storage.

    Screen capture showing pricing information for NVIDIA Quadro Virtual Workstation on Amazon Web Services Elastic Compute Cloud

  4. Select the most cost effective region and the EC2 instance type on which you want to deploy your GPU-accelerated virtual workstation. The only fulfillment option available for NVIDIA Quadro Virtual Workstation on Amazon Web Services Elastic Compute Cloud is 64-bit (x86) Amazon Machine Image (AMI).
  5. Click Continue to Subscribe.
  6. In the Subscribe to this software page that opens, click Accept Terms.
  7. When the subscription is complete, click Continue to Configuration.
  8. In the Configure this software page that opens, select the following options:
    • The software version of the NVIDIA vGPU software graphics driver that you want to run in your instance
    • The region where you want the instance to be deployed
    The only fulfillment option available for NVIDIA Quadro Virtual Workstation on Amazon Web Services Elastic Compute Cloud is 64-bit (x86) Amazon Machine Image (AMI)
  9. Click Continue to Launch.
  10. On the Launch this software page that opens, from the Choose Action drop-down list, select the action for launching the instance.
    • To launch the instance from the Launch this software page, select Launch from Website.

      If you select this option, the other options remain on this page to enable you to configure the instance from this page.

    • To launch the instance from the Amazon EC2 console page, select Launch through EC2.

      If you select this option, the other options are removed from this page to enable you to configure the instance by using the Launch Instance wizard.

  11. Configure and launch the instance.

    When prompted, ensure that you create or add a key pair to the set of keys authorized for this instance. If you proceed without a key pair, you will not be able to log in to the instance.

    When the instance is launched, a confirmation page is displayed with a link to the instance on the EC2 Console.

    Screen capture showing confirmation in the Launch this software page that the deployment is complete

  12. In the launch confirmation page, follow the link to your instance on the EC2 Console to confirm that the instance is running and that all status checks are completed.
  13. If you are creating a Windows instance and want to connect to the instance through RDP, edit the instance's security group to add an RDP security rule to open port 3389 for TCP connections.

Follow the instructions for your chosen OS to connect to the instance:

After connecting to the instance, verify that it was created properly as explained in Verifying the Creation of your GPU-Accelerated Virtual Workstation

1.2. Connecting to a GPU-Accelerated Virtual Workstation on a Windows VM Instance

Note: For instructions for a Linux VM, see Connect to Your Linux Instance in Amazon EC2 User Guide for Linux Instances.
  1. In the list of instances on the EC2 Dashboard, select the instance and click Connect.
  2. In the Connect to Your Instance window that opens, download the RDP file and get the password for connecting to your instance.
    1. Click Download Remote Desktop File.
    2. Click Get Password.
    3. When prompted, specify the path to the key pair file that is associated with this instance and click Decrypt Password.


    Screen capture showing the Connect to Your Instance window

  3. When the remote desktop file is downloaded, double-click the file to start a Remote Desktop Connection session on the VM.
  4. If you are warned that the publisher of the remote connection cannot be identified and are asked about whether to connect anyway, click Connect.
  5. When you are prompted, log in to the VM with the user name Administrator and the password that you got earlier.
  6. If you are warned that the publisher of the remote connection cannot be identified and are asked about whether to connect anyway, click Yes.
  7. Close the Connect to Your Instance window.
After connecting to your GPU-accelerated virtual workstation, verify that it was created properly as explained in Verifying the Creation of your GPU-Accelerated Virtual Workstation.

1.3. Verifying the Creation of your GPU-Accelerated Virtual Workstation

After connecting to your GPU-accelerated virtual workstation, verify that it was created properly by listing its GPUs. On a Windows VM instance you can also use NVIDIA Control Panel to verify that the NVIDIA driver is running.
After verifying the creation of your GPU-accelerated virtual workstation, you are now ready to run your design and engineering software.

1.3.1. Verifying the Creation of a GPU-Accelerated Virtual Workstation on a Windows VM Instance

  1. Open a command prompt window and change to the folder that contains the nvidia-smi command.
    C:\Users\Administrator>cd C:\Program Files\NVIDIA Corporation\NVSMI
  2. List the GPUs in your GPU-accelerated virtual workstation by running the nvidia-smi command without any options. The following example shows the output from nvidia-smi for a Windows VM instance configured with four NVIDIA V100 GPUs.
    C:\Program Files\NVIDIA Corporation\NVSMI>nvidia-smi
    Fri Jul 12 01:33:40 2019
    +-----------------------------------------------------------------------------+
    | NVIDIA-SMI 425.31       Driver Version: 425.31       CUDA Version: 10.1     |
    |-------------------------------+----------------------+----------------------+
    | GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
    | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
    |===============================+======================+======================|
    |   0  Tesla V100-SXM2... WDDM  | 00000000:00:1B.0 Off |                    0 |
    | N/A   42C    P0    37W / 300W |    343MiB / 16384MiB |      1%      Default |
    +-------------------------------+----------------------+----------------------+
    |   1  Tesla V100-SXM2... WDDM  | 00000000:00:1C.0 Off |                    0 |
    | N/A   41C    P0    38W / 300W |    239MiB / 16384MiB |      0%      Default |
    +-------------------------------+----------------------+----------------------+
    |   2  Tesla V100-SXM2... WDDM  | 00000000:00:1D.0 Off |                    0 |
    | N/A   43C    P0    40W / 300W |    239MiB / 16384MiB |      0%      Default |
    +-------------------------------+----------------------+----------------------+
    |   3  Tesla V100-SXM2... WDDM  | 00000000:00:1E.0 Off |                    0 |
    | N/A   42C    P0    38W / 300W |    239MiB / 16384MiB |      0%      Default |
    +-------------------------------+----------------------+----------------------+
    
    +-----------------------------------------------------------------------------+
    | Processes:                                                       GPU Memory |
    |  GPU       PID   Type   Process name                             Usage      |
    |=============================================================================|
    |    0      1256    C+G   Insufficient Permissions                   N/A      |
    |    0      1536    C+G   ...t_cw5n1h2txyewy\ShellExperienceHost.exe N/A      |
    |    0      4244    C+G   C:\Windows\explorer.exe                    N/A      |
    |    0      4340    C+G   Insufficient Permissions                   N/A      |
    |    0      5724    C+G   ...dows.Cortana_cw5n1h2txyewy\SearchUI.exe N/A      |
    |    0      6044    C+G   Insufficient Permissions                   N/A      |
    +-----------------------------------------------------------------------------+
  3. Start NVIDIA Control Panel to verify that the NVIDIA driver is running.
    1. Right-click on the desktop.
    2. From the menu that opens, choose NVIDIA Control Panel.
  4. In the NVIDIA Control Panel, from the Help menu, choose System Information to get information about the GPU.

    NVIDIA Control Panel reports the GPU that is being used, its capabilities, and the NVIDIA driver version that is loaded.



    Screen capture showing the verification of NVIDIA driver operation using NVIDIA Control Panel

1.3.2. Verifying the Creation of a GPU-Accelerated Virtual Workstation on a Linux VM Instance

List the GPUs in your GPU-accelerated virtual workstation by running the nvidia-smi command without any options.

The following example shows the output from nvidia-smi for a Linux VM instance configured with four NVIDIA V100 GPUs.

ubuntu@ip-172-31-16-135:~$nvidia-smi
Fri Jul 12 01:47:40 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 425.31       Driver Version: 425.31       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2... WDDM  | 00000000:00:1B.0 Off |                    0 |
| N/A   42C    P0    37W / 300W |    343MiB / 16384MiB |      1%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla V100-SXM2... WDDM  | 00000000:00:1C.0 Off |                    0 |
| N/A   41C    P0    38W / 300W |    239MiB / 16384MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla V100-SXM2... WDDM  | 00000000:00:1D.0 Off |                    0 |
| N/A   43C    P0    40W / 300W |    239MiB / 16384MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla V100-SXM2... WDDM  | 00000000:00:1E.0 Off |                    0 |
| N/A   42C    P0    38W / 300W |    239MiB / 16384MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
ubuntu@ip-172-31-16-135:~$

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